Researchers Have Found A Way To Spot Fake Online Reviews

Sometimes searching for hotel online feels like a blind date:
You've heard the guy is awesome, but there's no telling what
he'll be like when you actually meet.

A team of researchers from the State University of New York,
Stony Brook, might have come up with a way to solve the problem,
reports Technology Review's Neil
Savage. Rather than examine individual reviews, they
devised a technique that sniffs out the fakes by "pinpointing
where the densities of false reviews are for any given hotel,"
said Yejin Choi, assistant professor of computer science at the
university.

Here's how: When plotted on a graph, reviews typically produce a
pattern that resembles the letter J. That's because when
something is "scored from one to five stars," said Savage, "it
should have a relatively high amount of one-star reviews, fewer
twos, threes, and fours, and then a high number of five-star
ratings."

To spot the discrepancy, researchers compared ratings written by
frequent reviewers to those from single-time posters to see if
the latter were unusually glowing. The larger the gap between
negative and positive reviews, the more the J was
disrupted—proving the hotel was suspect.

Another tip-off was using too many superlatives, or posting
several times within a short time span, often the sign of a
marketing campaign.

For consumers, the technology might bring a new age of online
booking—that is, if review sites like Yelp and TripAdvisor adopt
it. We'd book more confidently knowing the real reviews, and
perhaps save some money as well.